1. Field of the Invention
The invention relates to the field of hearing aids. The invention, more specifically, relates to a hearing aid having an adaptive filter for generating a feedback cancellation signal, to a method of reducing acoustic feedback of a hearing aid and to a hearing aid circuit.
2. The Prior Art
Acoustic feedback occurs in all hearing instruments when sounds leak from the vent or seal between the ear mould and the ear canal. In most cases, acoustic feedback is not audible. But when in-situ gain of the hearing aid is sufficiently high or when a larger than optimal size vent is used, the output of the hearing aid generated within the ear canal can exceed the attenuation offered by the ear mould/shell. The output of the hearing aid then becomes unstable and the once-inaudible acoustic feedback becomes audible, i.e. in the form of a whistling or howling noise. For many users and people around, such audible acoustic feedback is an annoyance and even an embarrassment. In addition, hearing instruments that are at the verge of howling, i.e. show sub-oscillatory feedback, may corrupt the frequency characteristic and may exhibit intermittent whistling. Acoustic feedback is in particular an important problem in CIC (Complete In the Canal) hearing aids with a vent opening since the vent opening and the short distance between the output and the input transducers of the hearing aid lead to a low attenuation of the acoustic feedback path from the output transducer to the input transducer, and the short delay time maintains correlation in the signal.
To suppress undesired feedback it is well-known in the art to include an adaptive filter in the hearing aid to compensate for the feedback. The adaptive filter estimates the transfer function from output to input of the hearing aid including the acoustic propagation path from the output transducer to the input transducer. The input of the adaptive filter is connected to the output of the hearing aid, and the output signal of the adaptive filter is subtracted from the input transducer signal to compensate for the acoustic feedback. A hearing aid of this kind is disclosed, e.g. in WO 02/25996 A1, which document is incorporated herein by reference. In such a system, the adaptive filter operates to remove correlation from the input signal. Some signals representing e.g. speech or music, however, are signals with significant auto-correlation. Thus, the adaptive filter can not be allowed to adapt too quickly since removal of correlation from signals representing speech or music will distort the signals, and such distortion is of course undesired. Therefore, the convergence rate of adaptive filters in known hearing aids is a compromise between a desired high convergence rate that is able to cope with sudden changes in the acoustic environment and a desired low convergence rate that ensures that signals representing speech and music remain undistorted.
As adaptive feedback estimation filter one may employ a finite impulse response (FIR) filter, a warped filter such as a warped FIR filter or a warped infinite impulse response (IIR) filter etc. Such filter types are described in detail in the WO 02/25996 A1.
An overview of adaptive filtering is given in the textbook of Philipp A. Regalia: “Adaptive IIR filtering in signal processing and control”, published in 1995.
For a number of reasons, it may be desirable to equalize, or in the ideal case to whiten, the signals input to the adaptive feedback estimation filter. The advantages of signal equalization are particularly pronounced when a least mean square (LMS) type algorithm is utilized for feedback estimation.
Whitening of a signal is equivalent to orthogonalization or decorrelation of the FIR filter nodes corresponding to the autocorrelation matrix for the reference signal being transformed to a diagonal matrix having identical diagonal elements. This has certain useful consequences: The adaptation occurs at the same rate for all filter coefficients because the variance of each node is the same. The adaptation is generally faster as the performance is similar to that of an RLS (Recursive Least Squares) algorithm because there is no useful information in the second-order derivative of the underlying cost function as the autocorrelation matrix is a diagonal matrix. In addition, in some circumstances the adaptation error is also more evenly distributed over the frequency spectrum.
A further problem associated with adaptive feedback suppression in hearing aids is the following: For the same user, the acoustic feedback in hearing aids varies over time depending on yawning, chewing, talking, cerumen, etc. However, certain characteristics can be regarded as valid in most situations. Most notably, acoustic feedback is far weaker for frequencies below 1-1.3 kHz than at higher frequencies. Moreover, the problem of feedback is also limited at frequencies above 10 kHz as most hearing aid receivers produce little sound above this frequency. Additionally, most users have smaller hearing losses at lower frequencies than at higher frequencies. Thus, the hearing aid gain tends to be low (or even zero) in some frequency ranges making these frequency ranges less subject to feedback problems. When designing a feedback canceling system, it therefore makes sense to somehow emphasize frequency ranges where the canceling must perform particularly well. This, however, conflicts with the desire to equalize or decorrelate a signal as described above. There is therefore the problem of finding the right balance between frequency equalization or whitening providing a desired decorrelation or orthogonalization of the adaptive filter input signal and the appropriate frequency weighting of the adaptive filter input signal removing frequencies not relevant for feedback suppression.